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COVID-19 Pandemic, Urban Resilience and Real Estate Prices: The Experience of Cities in the Yangtze River Delta in China

Author

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  • Chuanhao Tian

    (School of Public Affairs, Zhejiang University, Hangzhou 310058, China
    Center of Social Welfare and Governance, Zhejiang University, Hangzhou 310058, China)

  • Xintian Peng

    (School of Public Affairs, Zhejiang University, Hangzhou 310058, China)

  • Xiang Zhang

    (School of Public Affairs, Zhejiang University, Hangzhou 310058, China
    Center of Social Welfare and Governance, Zhejiang University, Hangzhou 310058, China)

Abstract

The COVID-19 pandemic has severely impacted the urban real estate market around the world. This study regards the impact of the pandemic as a quasi-natural experiment, using the Difference in Difference model (DID) to examine the short-term impact of this severe public health crisis on the residential land and housing markets in the Yangtze River Delta. The study found that the COVID-19 pandemic has had a significant inhibitory effect on the average price of urban residential land and houses in the Yangtze River Delta. Although the currency oversupply has caused real estate prices in all cities to rise, the price of urban residential land decreased by 13.7% for each additional unit of epidemic severity. The greater the city’s resilience to the pressure of the COVID-19 pandemic, the faster its residential land prices will recover. Empirical research on the new house samples confirmed this conclusion. Local governments should continue to improve their ability to manage abnormal conditions, not only to prevent the spread of the epidemic, but also to gradually promote the recovery of the urban economy, strengthen urban resilience to better respond to health crises, and achieve sustainable urban development.

Suggested Citation

  • Chuanhao Tian & Xintian Peng & Xiang Zhang, 2021. "COVID-19 Pandemic, Urban Resilience and Real Estate Prices: The Experience of Cities in the Yangtze River Delta in China," Land, MDPI, vol. 10(9), pages 1-17, September.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:9:p:960-:d:633288
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    References listed on IDEAS

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    Cited by:

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    2. Raul-Tomas Mora-Garcia & Maria-Francisca Cespedes-Lopez & V. Raul Perez-Sanchez, 2022. "Housing Price Prediction Using Machine Learning Algorithms in COVID-19 Times," Land, MDPI, vol. 11(11), pages 1-32, November.
    3. Shian Zeng & Chengdong Yi, 2022. "Impact of the COVID-19 pandemic on the housing market at the epicenter of the outbreak in China," SN Business & Economics, Springer, vol. 2(6), pages 1-20, June.
    4. Nicholas Apergis, 2022. "Residential Housing Prices, COVID-19 and the Role of the Vaccination Program: Evidence from US State Panel Data," International Real Estate Review, Global Social Science Institute, vol. 25(4), pages 461-478.
    5. Shangkun Yu & Ruili Wang & Xuejie Zhang & Yi Miao & Chengxin Wang, 2023. "Spatiotemporal Evolution of Urban Shrinkage and Its Impact on Urban Resilience in Three Provinces of Northeast China," Land, MDPI, vol. 12(7), pages 1-22, July.
    6. Kowalski Michał J. & Wang Tong & Kazak Jan K., 2023. "The Impact of Covid-19 Pandemic on Value Migration Processes in the Real Estate Sector," Real Estate Management and Valuation, Sciendo, vol. 31(1), pages 10-24, March.

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